This is the version you keep within reach. Open it when another AI tool shows up, and come back to it whenever you feel like you're falling behind. It walks you through assembling a narrow toolkit and a simple filter for new releases, so you spend time on what actually solves your problem and drop the rest without a second thought.
The rule in one sentence: a narrow toolkit beats a wide one — you're investing in how you work, not in an app's name.
Before you start: two terms
Two words come back throughout this guide, so it's worth having them settled up front.
- Agent — an AI-based program that doesn't just answer questions but carries out multi-step tasks: it reads files, calls other tools, and does something on your behalf.
- Automation — a setup where such an agent runs a repeatable process on its own, without you present at every step.
A third term will also come in handy, since it resurfaces around specialists. API is how one tool connects to another — a kind of socket that programs plug into. It's what lets an agent fire off a search engine or an image generator by itself, instead of asking you to do it.
What you should have after this step: clarity that everything below refers to tools that do tasks, not just talk about them.
Step 1. Start from the core, not a shopping list
A daily core is a handful of items, and two of them alone would cover a full working day. The rest are specialists you call in for one specific job, plus "trial" tools you don't need to take too seriously.
The set below is a sample arrangement, not a list to copy. Remember the proportion — a few tools in daily rotation — rather than the specific names. Names will change; in six months some of these will be called something else, or gone.
- Claude Code — the main workspace: the model works through coding and operational tasks, reads project files, and carries out steps inside a single directory.
- VS Code — the editor (IDE) where you write and organize project files. It's not an AI tool by itself; it's often a convenient place to run Claude Code from.
- Glido — speech-to-text dictation. Fast and private.
- Codex — an agent similar to Claude Code, run alongside it because its strengths cover the other's weak spots.
- Hermes — an agent that "wakes up on request" when you message it. Handy for working away from your computer, and simpler to set up than a full agent configuration.
- Perplexity and Grok — for research: searching the web and finding specific threads or posts, usually to feed an automation.
That's the whole core. Alongside it are specialists you call in for single tasks — image generation, voice cloning, pulling data from a specific service. You reach for them when you need them and set them aside otherwise. You don't need to know them now.
What you should have after this step: a short list of tools in daily rotation — the shorter, the less there is to learn, update, and keep track of.
Step 2. Build order that outlives any single tool
AI agents are just "wrappers." On the surface they differ from each other; underneath, they may run on different models, but they all do the same thing — they work inside your directory, the folder holding your project files.
That gives a practical conclusion: build an order that outlives any single tool. There's no telling which one will be best in a few months. What's certain is that if you keep files, notes, and processes in a clean, well-labeled folder, the next tool — whichever one shows up — can plug into it. Once a project is organized, you can point one agent at it, then another, and each will be able to work in it.
What you should have after this step: one organized project folder that any agent can plug into, without a rebuild every time you switch tools.
Step 3. Run a resilience test
Picture your main tool going down for a day — an outage, or access getting blocked.
- Check whether you can switch to another tool and keep working.
- If you can't, that's a signal not to build your whole workflow on a single provider.
- Add at least one backup tool to your set that can do the same job.
What you should have after this step: confidence that a one-day outage from a single provider doesn't stop your whole workflow.
Step 4. Pick the tool for the step, not "in general"
Every piece of your work is a process made of smaller steps. The right question isn't "which tool is best overall," it's "which one is best for this specific step, in this specific situation."
Example — producing one video, broken into steps:
| Step | Tool for it |
|---|---|
| Research | Perplexity |
| Content structure | an agent that knows your context |
| The script itself | a plain chat with the model |
| Thumbnail | an image generator |
| A small graphic effect | a different, narrower tool |
| Editing | a classic video editor, no AI at all |
Two conclusions follow. First: not every step in a process needs AI. Second: even the ones that do don't need the same tool.
What you should have after this step: a task broken into small steps, each with its own tool picked out — including steps that deliberately stay AI-free.
Step 5. Filter every new thing through three questions
When something new shows up, don't dive straight into learning it. Run it through this filter first.
- Does it solve a problem I have right now? Most of the time the answer is "no." If not — and the tool still looks interesting — just save a link for later. That's it. You don't need to learn anything today.
- If yes — test it on a real task, not a made-up one. Not a month of playing around, one genuine use. Make sure it isn't risky: don't test it on a mass email send or a rebuild of an important database. Pick something real but safe.
- After a week, ask outright: did it work out? If it genuinely solved your problem, move it into your daily toolkit. If not, set it aside. No regrets.
And one thing that takes a lot of pressure off: there's a difference between knowing something exists and knowing how to do it. Most of the time the first is enough. Watching a ten-minute video doesn't obligate you to spend the next day learning and reproducing everything it showed. You note that the tool exists, and come back to it only once you actually hit the problem it solves.
What you should have after this step: a decision — "learn it now" or "save the link for later" — made in a few minutes, not a few days.
Step 6. Measure productivity by output, not hours
To finish, three notes that tie the rest together.
- Every change costs something at the start. Every time you switch tool or process, expect a temporary dip in output, say around a fifth, because change always costs a little. The question is whether you end up higher than where you started once the dip passes, or just back where you began. A change is worth making only if it genuinely lifts you above your previous level.
- Productivity is output per hour, not hours worked. A twelve-hour day spent reading threads, watching content, and planning can produce less than four hours of work that actually moves things forward. Start the day with one specific goal and make sure everything after it leads there.
- Define your own overriding goal. Your goal is almost certainly different from someone else's. If you want to build a company that does one thing really well, most of the hot new releases aren't your path there, they're a distraction. The most common mistake is doing too many things at once.
What you should have after this step: one overriding goal and the habit of asking whether a given activity leads to it.
How to check it's working
The toolkit and the filter are working if you can check off everything below.
- Your daily rotation is a handful of tools, not a dozen, and it isn't growing on its own.
- Files, notes, and processes live in one organized folder that any agent can plug into.
- You have at least one backup tool in your set for when the main one goes down.
- Facing something new, you ask "which tool for this step," not "which is best overall."
- New releases go through the three questions, and most of them end up as a saved link "for later," not another evening of learning.
- You start the day with one goal and judge against it whether what you did moved things forward.
The whole thing in one sentence: it's not about having every tool, it's about having a narrow, proven toolkit, a clear goal, and a simple filter for what's new. That's enough to stop drowning in it.